TITLE: Elephants affect the spatial distribution of savannah trees
DATE: 2017-12-01
AUTHOR: John L. Godlee
====================================================================


I have been attempting to write some scripts that will hopefully 
serve me well as I progress through writing my PhD. As I'm looking 
at the spatial distribution of trees and their canopy properties in 
dry tropical woodlands/savannahs, I thought it would be good to 
learn how to effectively plot tree distributions in plots. So I got 
hold of some data which contains the lat-long coordinates of trees 
in two 25 ha permanent savannah plots, one of which is known to be 
home to elephants, and one which isn't. As always, the code I used 
is in R.

The data and an example script which I used can be found here.

  [here](https://johngodlee.xyz/files/elephants/elephant_data.zip)

First load the necessary packages:

    # Packages ----
    library(ggplot2)  # Plotting
    library(dplyr)  # Manipulating data
    library(readr)  # Importing data
    library(viridis)  # Colour schemes

Then load in the data:

    # Set working directory ----
    setwd(dirname(rstudioapi::getActiveDocumentContext()$path))

    # Import data ----
    # Tree locations and diameters
    tree_loc_diam_1_2_summ <- read.csv("tree_loc_diam_1_2.csv")

    # Plot bounding boxes
    plot_bbox_1 <- read_csv("plot_bb_1.csv")
    plot_bbox_2 <- read_csv("plot_bb_2.csv")

First I want to plot the trees according to their DBH (Diameter at 
Breast Height, ~1.3 m), to see if there is a difference between 
plots. I'll make a map, and a box plot:

    # Plot tree DBH as point size ----
    ggplot(tree_loc_diam_1_2_summ, aes(x = dec_lon,
        y = dec_lat,
        size = dbh_cm,
        colour = species)) +
    geom_point(alpha = 0.5) +
    theme(aspect.ratio = 1) +  # coord_map() doesn't work with 
facet_wrap()
    facet_wrap(~ plot, scales = "free") +
    theme(legend.position = "bottom")


    # DBH boxplots ----
    ggplot(tree_loc_diam_1_2_summ, aes(x = plot, y = dbh_cm)) +
        geom_boxplot()

  ![Bubble plot of 
trees](https://johngodlee.xyz/img_full/elephants/dbh_map.png)

  ![Boxplot of tree 
diameters](https://johngodlee.xyz/img_full/elephants/dbh_plot.png)

Now I want to create a map that shows how clustered together the 
trees are in any given plot. For this I use the handy 
stat_density2d geom from ggplot2, and fill according to ..level... 
Also I found I had to manually increase the size of the plot, 
otherwise the density shading polygons get clipped and look really 
messy.

    # Is there an effect of elephants on spatial clustering of 
trees? ----
    # Split data frames
    tree_loc_diam_1_summ <- tree_loc_diam_1_2_summ %>%
        filter(plot == "elephants")

    tree_loc_diam_2_summ <- tree_loc_diam_1_2_summ %>%
        filter(plot == "no_elephants")

    # Create heatmaps based on density of trees
    elephant_plot <- ggplot(tree_loc_diam_1_summ, aes(x = dec_lon, 
y = dec_lat)) +
        stat_density2d(aes(fill = ..level..), geom = "polygon") +
        scale_fill_viridis() +
        geom_polygon(data = plot_bbox_1, aes(x = dec_lon, y = 
dec_lat), fill = NA, colour = "black") +
        geom_point(size = 0.8) +
        xlim(min(plot_bbox_1$dec_lon) - 0.001, 
max(plot_bbox_1$dec_lon) + 0.001) +
        ylim(min(plot_bbox_1$dec_lat) - 0.001, 
max(plot_bbox_1$dec_lat) + 0.001) +
        xlab("Decimal Longitude") +
        ylab("Decimal Latitude") +
        theme_classic() +
        theme(legend.text = element_text(size = 10),
                    axis.text = element_text(size = 10)) +
        labs(fill = "Tree Density")

    no_elephant_plot <- ggplot(tree_loc_diam_2_summ, aes(x = 
dec_lon, y = dec_lat)) +
        stat_density2d(aes(fill = ..level..), geom = "polygon") +
        scale_fill_viridis() +
        geom_polygon(data = plot_bbox_2, aes(x = dec_lon, y = 
dec_lat), fill = NA, colour = "black") +
        geom_point(size = 0.8) +
        xlim(min(plot_bbox_2$dec_lon) - 0.001, 
max(plot_bbox_2$dec_lon) + 0.001) +
        ylim(min(plot_bbox_2$dec_lat) - 0.001, 
max(plot_bbox_2$dec_lat) + 0.001) +
        xlab("Decimal Longitude") +
        ylab("Decimal Latitude") +
        theme_classic() +
        theme(legend.text = element_text(size = 10),
                    axis.text = element_text(size = 10)) +
        labs(fill = "Tree Density")

  ![Heatmap of trees with 
elephants](https://johngodlee.xyz/img_full/elephants/elephant_plot.p
ng)

  ![Heatmap of trees without 
elephants](https://johngodlee.xyz/img_full/elephants/no_elephant_plo
t.png)

The spatial clustering of trees in a plot with elephant activity 
(left) and without elephant activity (right). Elephants clearly 
have caused spatial clustering of trees.